Melanoma patients are very frequently diagnosed with putative second primaries. Indeed, some patients experience multiple occurrences of the disease. While these phenomena could be explained by strong genetic predisposition, it is also possible that a significant subset of these second and higher-order primaries are actually (clonal) recurrences of the initial primary, since many studies in other sites have occasionally confirmed a clonal origin for new tumors that are presumed to be independent on the basis of classical pathological criteria. Accurate classification of subsequent primaries has important clinical implications, but it is also of considerable relevance for epidemiologic research, since patients with multiple primaries are increasingly being recognized as an important resource, especially for studies of rare genetic factors. Our goal in this study is to conduct a pilot clonality investigation in patients diagnosed with double primary melanoma. Specifically, in order to identify molecular differences and similarities between tumors we propose to: (1) compare the mutational profiles of pairs of primary melanomas from individual patients with double malignancies using micro-satellite instability markers; and (2) reproduce the strategy in Aim 1 using array CGH rather than candidate markers. We will test 25 sets of first and second primary lesions from individuals diagnosed with double primary melanoma. This study will be the first to assess evidence for clonality in multiple primary melanoma. Our results will have implications for the pathologic classification of melanoma, clinical decision making for a patient with a second primary, and epidemiologic research methods. If results from this study suggest that cutaneous metastases are frequently diagnosed as second malignancies, then we will plan a subsequent study using the large population-based resource of tumor tissues from patients with double primary melanoma collected from the international population-based GEM Study (CA83180), designed to determine definitively the frequency of mis-diagnosis, and to determine predictors of tumors that would benefit from mutational profiling to validate the diagnosis. [unreadable] [unreadable] [unreadable]